Turn AI adoption into a governed operating program.
Kairro Governance connects live usage, findings, approvals, and framework posture so teams can review AI adoption with real operating context instead of isolated paperwork.
Why AI Governance Matters
Fragmented AI usage, disconnected approvals, and unclear control ownership make governance hard to operate at scale.
Fragmented tools
No shared investigation context
Evidence scattered across teams
No consistent approvals
AI Governance Model
Structured entities that mirror how enterprise teams actually review, approve, and monitor AI adoption.
Reviews and use cases
Track proposed and approved AI usage with owner, purpose, data handling, tools, sensitivity, and stage history.
Risk and posture
Use findings, live signals, governance state, and framework posture to understand where the program stands now.
Stages and reviewers
Move items through review stages, teams, and decisions with a clear audit trail instead of scattered tickets.
Framework controls
Connect governance work to controls, evidence, and maturity so review outcomes tie back to measurable posture.
Inventory and managed surfaces
Keep browser, collector, tool, and discovered AI usage tied to ownership and governance state.
Shadow AI and findings
Use shadow detections and findings to drive governance attention toward real usage, not just self-reported plans.
Governance Dashboard
Unified view of control posture, live findings, shadow AI, and governance progress.
Combine findings, policy outcomes, shadow AI, and governance state to understand where the program needs attention.
Track framework coverage, evidence, and control maturity without separating governance from the rest of the operating view.
Watch items in review, high-risk findings, shadow AI trends, and control gaps from the same screen.
End-to-End Governance Workflows
A traceable lifecycle from live detection through review, control alignment, and follow-through.
Discover and catalog
Use browser and collector telemetry, findings, and shadow AI to understand what is actually happening.
Assess and review
Assign owners, route to reviewers, and make decisions with live evidence attached.
Monitor and enforce
Use findings, policy outcomes, and device posture to keep the program aligned with how teams are actually using AI.
Improve and audit
Close the loop with framework controls, evidence, audit history, and control maturity updates.
Why Kairro’s Governance Stands Out
Governance stays connected to findings, policies, integrations, framework controls, and the live operating environment.
Continuously informed by browser telemetry, collector posture, findings, and shadow AI discovery.
Review history, control tracking, evidence, and scoring remain visible without leaving the platform.
The Result
Kairro turns AI adoption from a security risk into a governed, compliant, scalable program.